Ultra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation

Brunner, Andreas-David; Thielert, Marvin; Vasilopoulou, Catherine G.; Ammar, Constantin; Coscia, Fabian; Mund, Andreas; Hoerning, Ole; Bache, Nicolai; Apalategui, Amalia; Lubeck, Markus; Richter, Sabrina; Fischer, David; Raether, Oliver; Park, Melvin A.; Meier, Florian; Theis, Fabian J.; Mann, Matthias

doi:10.15252/msb.202110798

Cited by 374 publications

(473 citation statements)

References 71 publications

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“…6d,j), which in the case of timsTOF SCP allowed quantifying about 1,000 proteins per cell while using about 10min of total instrument time (only 5min of active gradient) per single cell. Thus, plexDIA increases sample throughput by 3-12 fold over the top performing single-cell proteomics methods that do not utilize isobaric mass tags 46, 47 .…”

Section: Resultsmentioning

confidence: 99%

Increasing the throughput of sensitive proteomics by plexDIA

Derks

Leduc

Huffman

et al. 2021

Preprint

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Current mass-spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. We aimed to increase the throughput of high-sensitivity proteomics while achieving high proteome coverage and quantitative accuracy. We developed a general experimental and computational framework, plexDIA, for simultaneously multiplexing the analysis of both peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. Specifically, plexDIA using 3-plex nonisobaric mass tags enables quantifying 3-fold more protein ratios among nanogram-level samples. Using 1 hour active gradients and first-generation Q Exactive, plexDIA quantified about 8,000 proteins in each sample of labeled 3-plex sets. Furthermore, plexDIA increases the consistency of protein quantification, resulting in over 2-fold reduction of missing data across samples. We applied plexDIA to quantify proteome dynamics during the cell division cycle in cells isolated based on their DNA content. The high sensitivity and accuracy of plexDIA detected many classical cell cycle proteins and discovered new ones. These results establish a general framework for increasing the throughput of highly sensitive and quantitative protein analysis.

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Section: Resultsmentioning

confidence: 99%

Increasing the throughput of sensitive proteomics by plexDIA

Derks

Leduc

Huffman

et al. 2021

Preprint

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“…In search of improved detection sensitivity for limited sample amounts, the implementation of ultra-low flow (ULF) ESI-MS has seen quite a revival in the last few years. Major progress has been documented when ULF (flow rates below 100 nL/min) was combined with ESI-MS 20,37–41 . Robust and routine operation at these low flow rates is however not straightforward and often required highly specialized LC systems or customized pre-column flow splitting configurations.…”

Section: Resultsmentioning

confidence: 99%

Deep proteome profiling with reduced carry over using superficially porous microfabricated nanoLC columns

Stejskal¹,

Beeck²,

Matzinger³

et al. 2021

Preprint

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In the field of LC-MS based proteomics, increases in sampling depth and proteome coverage have mainly been accomplished by rapid advances in mass spectrometer technology. The comprehensiveness and quality of data that can be generated do however also depend on the performance provided by nano liquid chromatography (nanoLC) separations. Proper selection of reversed-phase separation columns can be of paramount importance to provide the MS instrument with peptides at the highest possible concentration and separated at the highest possible resolution. As an alternative to traditional packed bed LC column technology that uses beads packed into capillary tubing, we present a novel LC column format based on photolithographic definition and Deep Reactive Ion Etching (DRIE) into silicon wafers. With a next generation pillar array column (μPAC) designed for universal use in bottom-up proteomics, the critical dimensions of the stationary phase support structures have been reduced by a factor of 2 to provide further increases in separation power. To demonstrate the potential for single-shot proteomics workflows, we report on a series of optimization and benchmarking experiments where we combine LC separation on a new generation of μPAC columns using Vanquish Neo UHPLC with fast Orbitrap Tribrid MS data-dependent acquisition (DDA) and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS). In addition to providing superior proteome coverage, robust operation over more than 1 month with a single nanoESI emitter and reduction of the column related sample carry over are additional figures of merit that can help improve proteome research sensitivity, productivity and standardization.

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“…For example, an increase of spatial resolution towards the single-cell level (1-10um/pixel) with current LC-MS workflows would reduce the detected depth of the proteome to 100s of proteins, limiting the conclusions to be drawn about the fine spatial resolution of the proteome in such tissues. Several single-cell proteomic methods have been recently described, but they do not yet use cells collected by LCM [51][52][53] . Novel high-throughput LC-MS platforms can now robustly analyse 1000s of samples relatively quickly [54][55][56] .…”

Section: Discussionmentioning

confidence: 99%

Deep topographic proteomics of a human brain tumour

Davis

Scott

Oetjen

et al. 2022

Preprint

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Cellular protein expression profiles within tissues are key to understanding disease pathology, and their spatial organisation determines cellular function. To precisely define molecular phenotypes in the spatial context of tissue, there is a need for unbiased, quantitative technology capable of mapping the expression of many hundreds to thousands of proteins within tissue structures. Here, we present a workflow for spatially resolved, quantitative proteomics of tissue that generates maps of protein expression across a tissue slice derived from a human atypical teratoid-rhabdoid tumour (AT/RT). We employ spatially-aware statistical methods that do not require prior knowledge of tissue structure to highlight proteins and pathways with varying spatial abundance patterns. We identify novel aspects of AT/RT biology that map onto the brain-tumour interface. Overall, this work informs on methods for spatially resolved deep proteo-phenotyping of tissue heterogeneity. Advanced spatially resolved tissue proteomics will push the boundaries of understanding tissue biology and pathology at the molecular level.

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Ultra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation

Cited by 374 publications

References 71 publications

Increasing the throughput of sensitive proteomics by plexDIA

Increasing the throughput of sensitive proteomics by plexDIA

Deep proteome profiling with reduced carry over using superficially porous microfabricated nanoLC columns

Deep topographic proteomics of a human brain tumour

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